1. Field of the Invention
The present invention relates generally to aircraft conflict detection and resolution.
2. Background
Aircraft traffic has been steadily increasing over the years. In particular, the air space in and around major population areas or other popular locations can be significantly congested. Added to this general increase in air traffic, are aspects such as the variety of aircraft with different sets of capabilities and preferences, restricted airspaces, and like factors that further aggravate the issues related to airspace congestion.
Conflict detection approaches for aircraft are designed to predict potential collisions between two or more aircraft. Conventional aircraft conflict detection approaches typically predict the path of a first aircraft for a predetermined look-ahead time interval, and determine whether a second aircraft is likely to come within a predetermined distance of the first aircraft during that time interval.
Conflict resolution methods address the issue of how a predicted aircraft conflict is avoided. Conventional aircraft conflict resolution typically involves one or both aircraft taking action to avoid the detected potential conflict by, for example, changing direction or changing speed.
Algorithms for Conflict Detection and Resolution (CD&R) systems have been widely studied. The methods used for CD&R can be broadly grouped into three categories: Probabilistic, Force Field, and Geometric. Probabilistic methods use uncertainties in the model to develop a set of possible future trajectories, each weighted by its probability of occurring. Force field methods model each aircraft as a charged particle and use modified electrostatic equations to determine resolution maneuvers. The “repulsive forces” between aircraft are used to define the maneuver each performs to avoid a collision. Even though this method provides a global (i.e., not restricted to pair-wise) solution to CD&R, several characteristics of this method make it difficult to incorporate in practical systems. Geometric CD&R methods use linear projections to predict aircraft trajectories as opposed to probabilistic or performance-based trajectories. They utilize positions and velocity vectors of aircraft involved in the encounter for collision detection by comparing velocity vectors of vehicles, and collision resolution/avoidance by providing encounter geometry to the resolution guidance algorithm.
Bilimoria, in “A Geometric Optimization Approach to Aircraft Conflict Resolution,” AIAA Guidance, Navigation, and Control Conference and Exhibit, Denver, Colo., 2000, presents a geometric optimization approach where the resolutions are optimal in the sense that they minimize the velocity vector changes required for conflict resolution. In Bilimoria's proposed approach, the resolutions are optimal for pair-wise encounter maneuvers, but not for multiple threat conflict encounter maneuvers. Dowek and Muñoz, in “Tactical Conflict Detection and Resolution in 3-D Airspace,” 4th USA/Europe Air Traffic Management R&D Seminar (ATM-2001), Santa Fe, N. Mex., 2001, presents KB3D, which is a tactical CD&R algorithm in a 3-D space for two aircraft that produces a set of solutions. KB3D is a state-based geometric CD&R algorithm. In CD&R-related literature, tactical algorithms use only state information to project aircraft trajectories and are intended to be used with short look-ahead times (a few minutes, typically 5-10) during which aircraft are likely to follow straight flight paths. KB3D computes independent maneuvers for the ownship (i.e., aircraft whose maneuvers are to be controlled by the CD&R system) each of which solves the conflict assuming that the ownship maneuvers.
As the airspace becomes more congested, the variety and capabilities of aircraft increase, and safer and/or better optimized air travel to reduce travel times and flight paths are sought, the problems of CD&R increase in relevance. As the demands of more crowded airspace intensify, it is desired that accurate potential conflict information is conveyed to the aircraft, while simultaneously reducing false alarms (e.g. unnecessary resolution advisories sent to aircraft). More accurate prediction of conflicts can be used advantageously in environments in which the aircraft that can potentially collide are both controllable, as well as in environments where only one of the aircraft (e.g. ownship) can be controlled in a manner to avoid the predicted collision.
What are needed therefore, are improved CD&R methods and systems that are more responsive and that can reduce false alarms.